The preference for residential independence among mature adults is a loiig-term trend in American society, where large proportions of older individuals choose to live alone or with a spouse, if married. However, for many individuals, poor health, chronic disability, and/or inadequate economic resources require alternative arrangements, such as combining households with other adults or making use of a patchwork of longterm care options. The purpose of this project is to investigate the role of health and functional ability for shaping residential and non- residential living arrangement choices of older Americans, with specific emphasis on the independent and joint effects of local community and state-level characteristics. Three research questions guide this project: (1) What combinations of specific health and social network characteristics influence current status and changes in residential independence? (2) How does the local health care service infrastructure and housing market environment influence the probability of maintaining residential independence? (3) How is the relationship between residential independence and personal and family resources altered when relevant features of the local community (e.g., health care service infrastructure and housing market conditions) are taken into account? These questions are addressed with panel data from the National Survey of Families and Households combined with county-level data from the US Census of Population and the Bureau of Health Relations' Area Resource Files. The analysis will be based on multivariate logistic regression techniques for multi-level data (Hierarchical Generalized Linear Models). Mixed (fixed effects and random effects) models are employed to estimate the individual and community factors that explain the underlying process in living arrangement choices. Employing these analytic techniques, we will also estimate accurately the joint effects of personal characteristics and community environment on residential living arrangement outcomes. In our model building, we pay particular attention to sample size issues and the potential for problems associated with endogeneity.